Highway Tunnel Defect Detection Based on Mobile GPR Scanning

Zhai, Junli; Wang, Qiang; Wang, Haozheng; Xie, Xu; Zhou, Mingyi; Yuan, Dongyang; Zhang, Weikang

doi:10.3390/app12063148

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Moreover, it has the ability to efficiently and precisely identify leaks in these tunnels. To solve the problem of defect detection in tunnels, Zhai et al [11] proposed a dual-frequency radar signal time-domain coherence calculation to suppress interference. Lei et al [12] proposed an on-board air-coupled GPR approach for high-speed railroad tunnel detection.…”

Section: Introductionmentioning

confidence: 99%

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Qiu,

Zhu,

Wang

et al. 2024

Meas. Sci. Technol.

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The multi vision metro tunnel defect sensing system mainly consists of IRT and RGB cameras, which can automatically identify and extract small tunnel lining surface defects, greatly improving detection efficiency. However, the presence of various issues like train vibration, inconsistent lighting, fluctuations in temperature and humidity leads to the images showing inadequate uniformity in illumination, blurriness, and a decrease in the level of detail. The above issues have led to unsatisfactory fusion processing results for multiple visual images and increased missed detection rates. A multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features is proposed. This method first takes the motion state of the train and the blurry image as constraints to eliminate dynamic blurring in the image. Secondly, Image weights are allocated based on the uniformity of visible light image illumination in the tunnel, as well as real-time temperature and humidity. Finally, image feature extraction and fusion are performed by a U-Net network that integrates channel attention mechanisms. The experimental results demonstrate that this approach improves the image pixel value variation rate by 39.7%, enhances the edge quality by 23%, and outperforms similar approach in terms of average gradient, gradient quality, and sum of difference correlation with improvements of 15.9%, 7.3%, and 26.6% respectively.

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Section: Introductionmentioning

confidence: 99%

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Qiu,

Zhu,

Wang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…The combination of multiple techniques [9,10] can especially enhance the identification and localization of the defects. Among these methods, GPR, particularly vehicle-mounted GPR [11], is more efficient and widely used in high-speed railway tunnel inspections [12]. However, the application of ground-coupled GPR is limited by the antenna-to-lining distance (within 20 cm) [13] and the need to avoid contact with the railway overhead line and complex control system, making it difficult to achieve a rapid and efficient inspection of the tunnel linings during the maintenance periods.…”

Section: Introductionmentioning

confidence: 99%

Application of Air-Coupled Ground Penetrating Radar Based on F-K Filtering and BP Migration in High-Speed Railway Tunnel Detection

Lei

Jiang

et al. 2023

Sensors

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As the number and length of high-speed railway tunnels increase in China, implicit defects such as insufficient lining thicknesses, voids, and poor compaction have become increasingly common, posing a serious threat to train operation safety. It is, therefore, imperative to conduct a comprehensive census of the defects within the tunnel linings. In response to this problem, this study proposes a high-speed railway tunnel detection method based on vehicle-mounted air-coupled GPR. Building on a forward simulation of air-coupled GPR, the study proposes the F-K filtering and BP migration algorithms based on the practical considerations of random noise and imaging interference from the inherent equipment. Through multi-dimensional quantitative comparisons, these algorithms are shown to improve the spectrum entropy values and instantaneous amplitude ratios by 4.6% and 11.6%; and 120% and 180%, respectively, over the mean and bandpass filtering algorithms, demonstrating their ability to suppress clutter and enhance the internal signal prominence of the lining. The experimental results are consistent with the forward simulation trends, and the verification using the ground-coupled GPR detection confirms that air-coupled GPR can meet the requirements of high-speed railway tunnel lining inspections. A comprehensive GPR detection model is proposed to lay the foundation for a subsequent defect census of high-speed railway tunnels.

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“…Since the 21st century, rapid development is experienced in tunnel construction [1,2]. However, various deficiencies such as lining cracks, pavement cracks, and water leakage have appeared as the service life of road tunnels increases [3,4]. The evaluation of tunnel health is the premise of tunnel maintenance and management.…”

Section: Introductionmentioning

confidence: 99%

Health State Assessment of Road Tunnel Based on Improved Extension Cloud Model

et al. 2023

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A scientifically accurate assessment of tunnel health is the prerequisite for the safe maintenance and sustainability of the in-service road tunnel. The changing trend of tunnel health is not considered in existing research. Most evaluation indicators are static and the ambiguities or randomness at the boundary of the health level intervals is neglected in most evaluation methods. In this paper, the evaluation index system combined with dynamic, and static is set to solve these problems. The changing trend of the health state of tunnels is analyzed through the cubic b-spline function. The weights of evaluation indicators are calculated based on the AHP-improved entropy method. The health evaluation method is proposed based on combing the extension theory and the cloud model improved by the cloud entropy optimization algorithm. Finally, the evaluation results of the proposed method are compared with the detection data of the Beilongmen Tunnel of Zhangzhuo Expressway. The results demonstrate that 80% of the evaluation results in the sample tunnel data are consistent with the standard results, and the remaining 20% show a lower level of health than the standard results. This reflects the evaluation results are impacted by the trend of tunnel health status changes. The health state can be more accurately evaluated by dynamic indicators. The improved extension cloud model is feasible and applicable in the health assessment of tunnels. This work provides innovative ideas for the evaluation of the health state of tunnels and theoretical support for the formulation of reasonable maintenance measures.

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Highway Tunnel Defect Detection Based on Mobile GPR Scanning

Cited by 5 publications

References 14 publications

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Application of Air-Coupled Ground Penetrating Radar Based on F-K Filtering and BP Migration in High-Speed Railway Tunnel Detection

Health State Assessment of Road Tunnel Based on Improved Extension Cloud Model

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